Methods and systems disclosed herein may include receiving signals along a traveled path over a period of time; recording signal power levels of the received signals over the period of time; receiving a first estimated track of the traveled path; identifying a feature of the received signal power levels, wherein the feature is caused by the signals having traveled different propagation paths; and generating a second estimated track based on the feature and the first estimated track.
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1. A method comprising: receiving signals, in a receiver from a transmitter, along a traveled path, wherein the traveled path is a path actually traveled by the receiver; storing, in a memory, a first estimated track, wherein the first estimated track includes an estimate of the traveled path of the receiver, recording, in a memory, signal power levels of the received signals, wherein the signal power levels include a first measured signal power level measured at a first time and a second measured signal power level measured at a second time, wherein the first time is before the second time; associating, in the memory, the first measured signal level power with the first time and associating the second measured signal power level with the second time; identifying, by a processor, an extracted change between the first measured signal power level associated with the first time and the second measured signal power level associated with the second time, wherein the extracted change is caused by a propagation path between the transmitter and the receiver transitioning from an unobstructed propagation path at the first time to an obstructed propagation path at the second time as the receiver moves along the traveled path from the first time to the second time, associating, in the memory, a first location on the first estimated track with the extracted change; storing, in the memory, a model including a model of an obstruction and a model of the transmitter; simulating, by the processor and based on the model, modeled signals from the model of the transmitter to points along the first estimated track to generate expected signal power levels of the modeled signals; identifying, by the processor, an expected change of the expected signal power levels, wherein the expected change is caused by a modeled propagation path transitioning from a modeled obstructed propagation path to a modeled unobstructed propagation path, storing, in the memory, an association between a second location on the first estimated track with the expected change; identifying, by the processor, the expected change as corresponding to the extracted change; generating a second estimated track, wherein the second estimated track is an estimate of the traveled path, based on the first location on the first estimated track associated with the extracted change and the second location of the first estimated track associated with the expected change; and storing the second estimated track in the memory, wherein the second estimated track includes smaller positional errors than the first estimated track relative to the traveled path.
A method corrects navigation tracks by receiving radio signals from a transmitter as a receiver moves along a path. The method records the signal power levels over time and stores an initial estimated track of the path. It then identifies a change in signal power caused by a transition from a clear to an obstructed signal path. This change is associated with a location on the initial track. A model of the obstruction and transmitter is used to simulate expected signal power levels along the initial track, identifying an expected change due to a modeled obstruction, also associated with a location on the initial track. By comparing the actual and expected signal power changes, a more accurate track is generated, reducing positional errors compared to the initial track.
2. The method of claim 1 , wherein the model of the obstruction includes a two-dimensional model of the obstruction.
The navigation track correction method from the previous description uses a simplified two-dimensional model of the obstruction when simulating expected signal power levels. This 2D model represents the physical shape or profile of the obstacle affecting signal propagation, aiding in the identification of expected signal changes. By using a 2D model of the obstruction, the computational complexity is reduced while still providing sufficient accuracy for track correction.
3. A method comprising: receiving signals in a receiver from a transmitter, along a traveled path, wherein the traveled path is a path actually traveled by the receiver; storing, in a memory, a first estimated track, wherein the first estimated track includes an estimate of the traveled path; recording, in the memory, signal power levels of the received signals; identifying, by a processor, an extracted feature of the signal power levels, wherein the extracted feature is caused by a propagation path between the transmitter and the receiver transitioning from a first propagation path to a second propagation path as a result of the receiver having traveled from a first point on the traveled path to a second point on the traveled path, wherein the first point is different than the second point; generating, by the processor, expected signal power levels of the received signals based on the first estimated track of the traveled path; generating, by the processor, a second estimated track based on the recorded signal power levels, the expected signal power levels, and the extracted feature; and storing, in the memory, the second estimated track, wherein the second estimated track is more accurate than the first estimated track relative to the traveled path.
A method refines a device's path using radio signals. It receives signals from a transmitter while moving along a path and saves both an initial estimated track and the received signal power levels. A processor identifies a feature in the signal power levels caused by the signal path changing (e.g., obstructed to clear). Using the initial track, it generates expected signal power levels. Based on the recorded signal power levels, the expected signal power levels, and the identified signal feature, it creates a more precise track. This refined track provides a more accurate representation of the actual path.
4. The method of claim 3 , wherein receiving the signals along the traveled path includes receiving the signals over a period of time, wherein recording signal power levels of the received signals includes recording the signal power levels of the received signals over the period of time, and wherein the extracted feature is caused by the signals having traveled different propagation paths to two different points on the traveled path at two different times.
In the path refinement method described above, signal power levels are recorded over a period of time as the device moves. The identified feature in the signal power levels is caused by the radio signals traveling different paths to the device at different times, leading to variations in signal strength. These variations, such as a signal weakening due to an obstruction, are used to improve the accuracy of the estimated track.
5. The method of claim 4 , further comprising: identifying an expected feature based on the expected signal power levels; determining a track bias based the extracted feature and the expected feature; and generating the second estimated track based on the track bias.
Building on the previous path refinement method, the process also identifies an expected feature in the predicted signal power levels. The difference between the actual and expected signal features is used to determine a track bias. This track bias represents the error between the initial estimate and the likely true path. The second, more accurate track is then generated based on this calculated track bias.
6. The method of claim 5 , further comprising identifying extracted features of the signal power levels, wherein the extracted features are caused by the signals having traveled different propagation paths to the traveled path; identifying expected features based on the expected signal power levels, wherein determining the track bias includes determining the track bias based the extracted features and the expected features; and generating the second estimated track based on the track bias.
The path refinement method from the previous description identifies multiple actual signal features and their corresponding expected signal features. These features arise from variations in signal propagation paths. By analyzing multiple features, the system more precisely determines the track bias, which accounts for the aggregate discrepancies between the expected and actual signal behaviors. The second track is then generated based on this improved bias, resulting in a more accurate path.
7. The method of claim 6 , wherein each of the extracted features is caused by the signals having traveled different propagation paths from a same transmitter to the traveled path; and wherein determining the track bias comprises determining the expected features that correspond to the extracted features.
In the path refinement method from the previous description, all the extracted signal features originate from a single transmitter. To refine the track bias, the system identifies which expected signal features correspond to the extracted signal features from that same transmitter. This ensures that the track bias is determined based on consistent signal behavior, improving the accuracy of the corrected path.
8. The method of claim 7 , further comprising: determining lines of position (LOPs) based on the expected features or based on the extracted features; advancing one or more of the LOPs based on locations associated with each of the extracted features; and determining the track bias based on the LOPs.
This invention relates to navigation systems, specifically methods for improving position accuracy by correcting track bias using feature-based positioning. The problem addressed is the inherent inaccuracy in navigation systems due to track bias, which arises from systematic errors in sensor measurements or environmental factors. The invention provides a solution by leveraging expected or extracted features from the environment to refine position estimates. The method involves determining lines of position (LOPs) based on either expected features (predefined reference points) or extracted features (detected in real-time). These LOPs represent possible positions of the navigation system relative to the features. The method then advances one or more of these LOPs based on the locations of the extracted features, effectively adjusting the position estimates to account for the observed data. Finally, the track bias is determined by analyzing the adjusted LOPs, allowing for corrections to be applied to the navigation system to improve accuracy. The invention enhances traditional navigation techniques by incorporating feature-based positioning, which provides additional constraints to reduce position errors. This approach is particularly useful in environments where traditional positioning methods, such as inertial navigation or dead reckoning, are prone to drift or bias. The method can be applied in various applications, including autonomous vehicles, robotics, and maritime navigation, where precise positioning is critical.
9. The method of claim 8 , further comprising: determining the track bias based on an intersection of two of the LOPs, or, determining the track bias based on an intersection of three or more of the LOPs and determining a confidence level of the track bias based on a distance between intersections of different pairs of the three or more of the LOPs.
The path refinement method described above calculates the track bias using intersections of Lines of Position (LOPs). The track bias is based on the intersection of two LOPs, or, if three or more LOPs are available, the track bias is based on the intersection of these LOPs. A confidence level for the track bias is determined based on the distances between the intersections of different pairs of the LOPs. Smaller distances indicate higher confidence.
10. The method of claim 6 , wherein identifying an extracted feature of the signal power levels further comprises: detecting an increase in the signal power levels indicating shifts in the propagation paths of the signals, wherein the increase in the signal power levels is indicative of an obstruction of one of the propagation paths relative to another one of the propagation paths, or detecting a decrease in the signal power levels indicating shifts in the propagation paths of the signals, wherein the decrease in the signal power levels is indicative of an obstruction of one of the propagation paths relative to another one of the propagation paths.
Within the path refinement method's feature identification process, increases or decreases in signal power levels are detected. These changes indicate shifts in the propagation paths of the signals. An increase suggests a new obstruction affecting a signal path, while a decrease indicates the opposite, influencing the path refinement.
11. The method of claim 10 , wherein further comprising: recording polarity of the received signals; and identifying an extracted feature of the polarity of the received signals, wherein the extracted feature of the polarity of the received signals is caused by the signals having traveled different propagation paths to two different points on the traveled path.
The path refinement method from the previous description also records the polarity of the received radio signals. An extracted feature of the polarity of the signals, also caused by signals traversing different paths to the receiver, is identified. This additional information further enhances the accuracy of the path correction process by accounting for changes in signal characteristics beyond just signal strength.
12. The method of claim 11 , wherein generating expected signal power levels of the received signals includes determining unobstructed direct electromagnetic wave propagation conditions from a transmitter to the traveled path and obstructed direct electromagnetic wave propagation conditions from a transmitter to the traveled path.
In the signal processing for path refinement, the method determines both unobstructed direct electromagnetic wave propagation conditions and obstructed direct electromagnetic wave propagation conditions from the transmitter. These conditions are used when generating the expected signal power levels, providing a more comprehensive model for comparison with the recorded signal power levels, which improves track accuracy.
13. The method of claim 11 further comprising: determining a bias region for the first estimated track; selecting one or more LOPs, based on the bias region, to advance; and determining the track bias based on the selected one or more selected LOPs.
The path refinement method from the previous description defines a bias region for the initial estimated track, representing an area of likely error. Based on this region, one or more Lines of Position (LOPs) are selected and advanced. The track bias is then determined based on these selected and advanced LOPs, focusing the correction on the area of greatest uncertainty to optimize path accuracy.
14. The method of claim 13 , further comprising: determining a plurality of biases; determining a final bias based on a sum of the plurality biases; and determining the second estimated track based on the sum of the plurality of biases.
In the path refinement method from the previous description, a plurality of biases are determined. A final bias is then calculated based on the sum of these individual biases. The second, refined track is subsequently determined based on this cumulative bias, allowing for a more comprehensive and accurate correction of the estimated path.
15. The method of claim 14 , further comprising: weighing one or more of the plurality of biases prior to summing the plurality of biases, or weighing one or more of the plurality of biases based on an age of the one or more LOPs or on a distance of the one or more LOPs from an estimated current position.
In the path refinement method from the previous description, when summing the plurality of biases, one or more of these biases are weighed. The weighing can be based on factors such as the age of the corresponding Line of Position (LOP) or the distance of the LOP from the estimated current position. This weighting strategy allows the system to prioritize more relevant or reliable biases, further enhancing the accuracy of the path correction.
16. The method of claim 3 , wherein receiving the signals along the traveled path includes receiving the signals at two different points along the traveled path at a same time, wherein recording signal power levels of the received signals includes recording the signal power levels of the received signals over at the two different points, and wherein the extracted feature is caused by the signals having traveled different propagation paths to the two different points on the traveled path.
This path refinement method receives radio signals at two different points along the path at the same time. The signal power levels are recorded at these two points. The extracted feature from the signal power levels is a result of signals traveling different paths to these two points, allowing the system to exploit spatial diversity to improve the accuracy of the refined track.
17. The method of claim 16 , further comprising: identifying an expected feature based on the expected signal power levels; determining a track bias based the extracted feature and the expected feature; and generating the second estimated track based on the track bias.
The path refinement method described above that receives signals at two points simultaneously, identifies an expected feature based on expected signal power levels. It determines a track bias based on the actual and expected signal features, and generates a second estimated track based on the track bias, creating a more accurate estimate of the path.
18. A device comprising: a receiver to receive signals along a traveled path from a transmitter, wherein the traveled path is a path actually traveled by the receiver; a memory to record signal power levels of the received signals and a first estimated track, wherein the first estimated track includes an estimate of the traveled path; a processor to: identify an extracted feature of the signal power levels, wherein the extracted feature is caused by a propagation path between the transmitter and the receiver transitioning from a first propagation path to a second propagation path as a result of the receiver having traveled from a first point on the traveled path to a second point on the traveled path, wherein the first point is different than the second point; generate expected signal power levels of the received signals based on the first estimated track of the traveled path; and generate an updated estimated track of the traveled path based on the recorded signal power levels, a first estimated track of the traveled path, the expected signal power levels, and the extracted feature, wherein the memory is configured to store the updated estimated track, wherein the updated estimated track is more accurate than the first estimated track relative to the traveled path.
A device corrects navigation tracks by receiving radio signals from a transmitter. It records signal power levels and an initial estimated track of the path in memory. A processor identifies a feature in the signal power caused by a signal path change, generates expected signal power levels based on the initial track, and produces a more accurate track based on the recorded signal power, the initial track, the expected signal power, and the identified feature. This updated track, stored in memory, is more precise than the initial estimate.
19. The device of claim 18 , wherein the receiver is configured to receive the signals over a period of time, wherein the memory records the signal power levels of the received signals over the period of time, wherein the extracted feature is caused by the signals having traveled different propagation paths to the two different points on the traveled path at two different times, and wherein the processor is configured to identify an expected feature based on the expected signal power levels, determine a track bias based the extracted feature and the expected feature, and generate the updated estimated track based on the track bias.
In the navigation device, the receiver captures signals over time. Signal power levels are recorded over time. The identified feature in the signal power is caused by the signals traveling different paths to two different points at two different times. The processor identifies an expected feature based on the expected signal power levels, determines a track bias from the actual and expected features, and generates the updated track based on the track bias, leading to a more accurate position.
20. The device of claim 19 , wherein the processor is further configured to identify extracted features of the signal power levels, wherein the extracted features are caused by the signals having traveled different propagation paths to the traveled path; identify expected features based on the expected signal power levels, wherein determining the track bias includes determining the track bias based the extracted features and the expected features; and generate the updated estimated track based on the track bias, wherein each of the extracted features is caused by the signals having traveled different propagation paths from a same transmitter to the receiver.
The navigation device from the previous description, the processor also identifies multiple signal features and their corresponding expected signal features. These features are caused by signals traveling different paths from the same transmitter. The track bias is calculated based on these multiple features, and the updated estimated track is generated based on this improved bias, providing a more accurate representation of the path.
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April 18, 2013
May 16, 2017
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